Review of Research on Vision-Based Parking Space Detection Method

Yong Ma, Yangguo Liu, Shiyun Shao, Jiale Zhao, Jun Tang

Source Title: International Journal of Web Services Research (IJWSR)19(1)

ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781799893462|DOI: 10.4018/IJWSR.304061

MLA

Ma, Yong, et al. "Review of Research on Vision-Based Parking Space Detection Method." IJWSR vol.19, no.1 2022: pp.1-25. http://doi.org/10.4018/IJWSR.304061

APA

Ma, Y., Liu, Y., Shao, S., Zhao, J., & Tang, J. (2022). Review of Research on Vision-Based Parking Space Detection Method. International Journal of Web Services Research (IJWSR), 19(1), 1-25. http://doi.org/10.4018/IJWSR.304061

Chicago

Ma, Yong, et al. "Review of Research on Vision-Based Parking Space Detection Method," International Journal of Web Services Research (IJWSR) 19, no.1: 1-25. http://doi.org/10.4018/IJWSR.304061

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Abstract

Parking space detection is an important part of the automatic parking assistance system. How to use existing sensors to accurately and effectively detect parking spaces is the key problem that has not been solved in the automatic parking system. Advances in Artificial Intelligence and sensing technologies have motivated significant research and development in parking space detection in the automotive field. Firstly, based on extensive investigation of a lot of literature and the latest re-search results, this paper divides parking space detection methods into methods based on traditional visual features and those methods based on deep learning and introduces them separately. Secondly, the advantages and disadvantages of each parking space detection method are analyzed, compared, and summarized. And the benchmark datasets and algorithm evaluation standards commonly used in parking space detection methods are introduced. Finally, the vision-based parking space detection method is summarized, and the future development trend is prospected.